Entrepreneurial Ecosystems as Complex Systems

Abstract

The concept of the entrepreneurial ecosystem has emerged as a central framework for understanding how regional contexts shape entrepreneurial activity and regional development. Despite its widespread adoption by academics and policymakers, the field remains critiqued for its "black box" nature: while the components of ecosystems are well-identified, the dynamic mechanisms and feedback loops that govern their evolution are poorly understood. Furthermore, the literature has struggled to bridge the divide between macro-level structures and micro-level agency.

This thesis advances a complex-systems understanding of entrepreneurial ecosystems by uncovering the mechanisms, feedback loops, and micro–macro linkages that connect ecosystem elements, entrepreneurial agents, and institutional conditions. It comprises three interconnected studies that combine mechanism-based synthesis, computational simulation, and qualitative causal-loop modelling.

The first study (Chapter 2) systematically maps the existing literature to uncover the interdependencies between ecosystem elements. It synthesizes fragmented findings into two fundamental macro-level feedback loops: the "Talent Accumulation Cycle" and the "Resource Accumulation Cycle". These provide a structural template for ecosystem dynamics.

The second study (Chapter 3) opens the black box from the bottom up. It develops an agent-based model (ABM) that embeds heterogeneous entrepreneurs within Scott's (2014) institutional pillars. This simulation demonstrates the microfoundations of ecosystem evolution, revealing how individual decisions aggregate to create emergent norms and path-dependent trajectories.

The third study (Chapter 4) grounds these insights in a specific deep-tech context. Through a qualitative system dynamics analysis of the Canadian space entrepreneurial ecosystem, it empirically identifies the high-leverage feedback loops that dominate the sector. It reveals the "Anchor-Customer Legitimacy Loop" as the system's primary engine and uncovers a "Grant Trap" where disconnected policy interventions unintentionally inhibit scaling.

Taken together, these studies advance a rigorous, complexity-based research program for entrepreneurial ecosystems. The thesis contributes a robust process theory of ecosystem co-evolution, demonstrates the value of methodological pluralism (combining systematic mapping, simulation, and causal mapping), and offers a systems-aware toolkit for policymakers to identify high-leverage intervention points beyond static support programs.